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Abstract: Diffusion tensor imaging (DTI) is achieved by collecting a series of diffusion-weighted images (DWIs). Signal averaging of multiple repetitions can be performed in the k-space (k-avg) or in the image space (m-avg) to improve the image quality. Alternatively, one can treat each acquisition as an independent image and use all of the data to reconstruct the DTI without doing any signal averaging (no-avg). To compare these three approaches, in this study, in vivo DTI data were collected from five normal mice. Noisy data with signal-to-noise ratios (SNR) that varied between five and 30 (before averaging) were then simulated. The DTI indices, including relative anisotropy (RA), trace of diffusion tensor (TR), axial diffusivity (λ║), and radial diffusivity (λ⊥), derived from the k-avg, m-avg, and no-avg, were then compared in the corpus callosum white matter, cortex gray matter, and the ventricles. We found that k-avg and m-avg enhanced the SNR of DWI with no significant differences. However, k-avg produced lower RA in the white matter and higher RA in the gray matter, compared to the m-avg and no-avg, regardless of SNR. The latter two produced similar DTI quantifications. We concluded that k-avg is less preferred for DTI brain imaging. [Copyright &y& Elsevier]

Abstract: Keyhole diffusion tensor imaging (keyhole DTI) was previously proposed in cardiac imaging to reconstruct DTI maps from the reduced phase-encoding images. To evaluate the feasibility of keyhole DTI in brain imaging, keyhole and zero-padding DTI algorithms were employed on in vivo mouse brain. The reduced phase-encoding portion, also termed as the sharing rate, was varied from 50% to 90% of the full k-space. Our data showed that zero-padding DTI resulted in decreased fractional anisotropy (FA) and decreased mean apparent diffusion coefficient (mean ADC) in white matter (WM) regions. Keyhole DTI showed a better edge preservation on mean ADC maps but not on FA maps as compared to the zero-padding DTI. When increasing the sharing rate in keyhole approach, an underestimation of FA and an over- or underestimation of mean ADC were measured in WM depending on the selected reference image. The inconsistency of keyhole DTI may add a challenge for the wide use of this modality. However, with a carefully selected directive diffusion-weighted image to serve as the reference image in the keyhole approach, this study demonstrated that one may obtain DTI indices of reduced-encoding images with high consistency to those derived with full k-space DTI. [ABSTRACT FROM AUTHOR]

• Correlation between MEMRI and DTI was found in P301L tau mice. • Axonal transport deficits in tauopathy were correlated with the loss of myelin. • Myelin loss may contribute to the axonal degeneration in tauopathy. Diffusion Tensor Imaging (DTI) and Manganese Enhanced MRI (MEMRI) are noninvasive tools to characterize neural fiber microstructure and axonal transport. A combination of both may provide novel insights into the progress of neurodegeneration. To investigate the relationship of DTI and MEMRI in white matter of tauopathy, twelve optic nerves of 11-month-old p301L tau mice were imaged and finished with postmortem immunohistochemistry. MEMRI was used to quantify Mn2+ accumulation rates in the optic nerve (ON, termed ONAR) and the Superior Colliculus (SC, termed SCAR), the primary terminal site of ON in mice. We found that both ONAR and SCAR revealed a significant linear correlation with mean diffusion (mD) and radial diffusion (rD) but not with other DTI quantities. Immunohistochemistry findings showed that ONAR, mD, and rD are significantly correlated with the myelin content (Myelin Basic Protein, p < 0.05) but not with the axonal density (SMI-31), tubulin density, or tau aggregates (AT8 staining). In summary, slower axonal transport appeared to have less myelinated axons and thinner remaining axons, associated with reduced rD and mD of in vivo DTI. A combination of in vivo MEMRI and DTI can provide critical information to delineate the progress of white matter deficits in neurodegenerative diseases. [ABSTRACT FROM AUTHOR]